Spatio-Temporal Treatment of Noisy Images Using Brushlets

1. A method for producing denoised multi-dimensional spatio-temporal image data comprising a plurality of multi-dimensional frames taken at different times, the method comprising: performing multi-dimensional, spatial brushlet filtering, in the frequency domain, of the plurality of multi-dimensional frames to generate a set of spatial brushlet coefficients; thresholding the set of spatial brushlet coefficients to produce a set of spatially-denoised image data corresponding to the multi-dimensional spatio-temporal image data; performing a first temporal brushlet filtering, in the time domain, of the spatially-denoised spatio-temporal image data to generate a first set of temporal brushlet coefficients; thresholding the first set of temporal brushlet coefficients to produce a first set of spatio-temporally denoised image data corresponding to the multi-dimensional spatio-temporal image data; performing a second temporal brushlet filtering, in the frequency domain, of the first set of spatio-temporally denoised image data to generate a second set of temporal brushlet coefficients; thresholding the second set of temporal brushlet coefficients to produce a second set of spatio-temporally denoised image data corresponding to the multi-dimensional spatio-temporal image data; and outputting the second set of spatio-temporally denoised image data; wherein the above said filtering steps are performed using a computer system.

2. The method of claim 1 , wherein the multi-dimensional spatio-temporal image data comprises three-dimensional spatio-temporal image data comprising two-dimensional frames taken at different instants in time.

3. The method of claim 1 , wherein the multi-dimensional spatio-temporal image data comprises four-dimensional spatio-temporal image data comprising three-dimensional frames taken at different instants in time.

4. The method of claim 1 , wherein producing denoised image data comprises removing speckle noise out of the image data.

5. The method of claim 1 , wherein producing denoised image data comprises denoising noisy ultrasound image data.

6. The method of claim 1 , wherein any of the thresholding steps comprises performing a hard thresholding operation on the respective coefficients.

7. The method of claim 1 , wherein any of the thresholding steps comprises performing a Minimax thresholding operation on the respective coefficients.

8. The method of claim 1 , further comprising segmentation of an image feature following denoising of the image data.

9. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for producing denoised multi-dimensional spatio-temporal image data comprising a plurality of multi-dimensional frames taken at different times, the method comprising: performing multi-dimensional, spatial brushlet filtering, in the frequency domain, of the plurality of multi-dimensional frames to generate a set of spatial brushlet coefficients; thresholding the set of spatial brushlet coefficients to produce a set of spatially-denoised image data corresponding to the multi-dimensional spatio-temporal image data; performing a first temporal brushlet filtering, in the time domain, of the spatially-denoised spatio-temporal image data to generate a first set of temporal brushlet coefficients; thresholding the first set of temporal brushlet coefficients to produce a first set of spatio-temporally denoised image data corresponding to the multi-dimensional spatio-temporal image data; performing a second temporal brushlet filtering, in the frequency domain, of the first set of spatio-temporally denoised image data to generate a second set of temporal brushlet coefficients; thresholding the second set of temporal brushlet coefficients to produce a second set of spatio-temporally denoised image data corresponding to the multi-dimensional spatio-temporal image data; and outputting the second set of spatio-temporally denoised image data.

10. The computer-readable medium of claim 9 , wherein the multi-dimensional spatio-temporal image data comprises three-dimensional spatio-temporal image data comprising two-dimensional frames taken at different instants in time.

11. The computer-readable medium of claim 9 , wherein the multi-dimensional spatio-temporal image data comprises four-dimensional spatio-temporal image data comprising three-dimensional frames taken at different instants in time.

12. The computer-readable medium of claim 9 , wherein producing denoised image data comprises removing speckle noise out of the image data.

13. The computer-readable medium of claim 9 , wherein producing denoised image data comprises denoising noisy ultrasound image data.

14. The computer-readable medium of claim 9 , wherein any of the thresholding steps of the method comprises performing a hard thresholding operation on the respective coefficients.

15. The computer-readable medium of claim 9 , wherein any of the thresholding steps of the method comprises performing a Minimax thresholding operation on the respective coefficients.

16. The computer-readable medium of claim 9 , wherein the method further comprises segmentation of an image feature following denoising of the image data.